Answer:
10.5774194, you can round up as many ways as you want.
14.
Angles 4 and 6 are supplementary, because they are on the same line. Supplementary angles add up to 180 degrees, and a line must be 180 degrees.
15.
Angles 1 and 8 are congruent, because they are alternate exterior angles
16.
m = y2 - y1 / x2 - x1
m = 7 - 2 / 4 - 5
m = 5 / -1
m = -5
17.
m = 3 - 3 / 7 - (-5)
m = 0 / 12
m = 0
18.
m = 1 - (-2) / 5 - (-4)
m = 3 / 9
m = 1/3
19.
A = (0, 3) - B = (3,0)
m = 0 - 3 / 3 - 0
m = -3 / 3
<em>m = -1</em>
C = (0, -2) - D = (4, 2)
m = 2 - (-2) / 4 - 0
m = 4 / 4
<em>m = 1</em>
Perpendicular, because the slopes are opposite reciprocals.
20.
E = (1, 2) - F = (0, 0)
m = 0 - 2 / 0 - 1
m = -2 / -1
<em>m = 2</em>
G = (1, -3) - H = (3, 0)
m = 0 - (-3) / 3 - 1
<em>m = 3 / 2</em>
Neither, because the slopes are different.
21.
I = (0, 1) - J = (2, -4)
m = -4 - 1 / 2 - 0
<em>m = -5/2</em>
K = (-1, -2) - L = (4, 0)
m = 0 - (-2) / 4 - (-1)
<em>m = 2/5</em>
Perpendicular, because the slopes are opposite reciprocals.
22.
M = (-2, 2) - N = (2, 2)
Horizontal line
<em>m = 0</em>
O = (3, 0) - P = (-3, 0)
Horizontal line
<em>m = 0
</em>Parallel, because the slopes are the same.
<em>
</em>23.
Angle 2 is congruent to angle 1 because of the alternate exterior angle theorem.
Angle 1 is congruent to angle 3 because of the vertical angle theorem.
Angle 2 is congruent to angle 3 because of substitution.
Line l is parallel to line m because the corresponding angles are congruent.
Answer:
8
Step-by-step explanation:
The equation is of the form
y = kx ← k is the constant of proportionality
To find k use the slope formula
k = ( y₂ - y₁ ) / ( x₂ - x₁ )
with (x₁, y₁ ) = (0, 0) and (x₂, y₂ ) = (2, 16) ← 2 points on the line
k = 
= 
= 8
Answer:
E(w) = 1600000
v(w) = 240000
Step-by-step explanation:
given data
sequence = 1 million iid (+1 and +2)
probability of transmitting a +1 = 0.4
solution
sequence will be here as
P{Xi = k } = 0.4 for k = +1
0.6 for k = +2
and define is
x1 + x2 + ................ + X1000000
so for expected value for W
E(w) = E( x1 + x2 + ................ + X1000000 ) ......................1
as per the linear probability of expectation
E(w) = 1000000 ( 0.4 × 1 + 0.6 × 2)
E(w) = 1600000
and
for variance of W
v(w) = V ( x1 + x2 + ................ + X1000000 ) ..........................2
v(w) = V x1 + V x2 + ................ + V X1000000
here also same as that xi are i.e d so cov(xi, xj ) = 0 and i ≠ j
so
v(w) = 1000000 ( v(x) )
v(w) = 1000000 ( 0.24)
v(w) = 240000
